class_docstr: EfficientNet head: 1x1, BN, AF, AvgPool, Dropout, FC.
code: def forward(self, x):
      x = self.conv_af(self.conv_bn(self.conv(x)))
      x = self.avg_pool(x)
      x = x.view(x.size(0), -1)
      x = self.dropout(x) if self.dropout else x
      x = self.fc(x)
      return x
  
imports: from pycls.core.config import cfg
  from pycls.models.blocks import activation, conv2d, conv2d_cx, drop_connect, gap2d, gap2d_cx, init_weights, linear, linear_cx, norm2d, norm2d_cx, SE
  from torch.nn import Dropout, Module
label_desc: Use image node_id 2 for calling the EffHead obj's underlying member method code with example usage: obj.forward(x) and returns: x